1. Field of the Invention
The present invention relates to a road surface state estimating apparatus, a road surface friction state estimating apparatus, a road surface state physical quantity calculating apparatus, and a road surface state announcing apparatus. In particular, the invention relates to a road surface state estimating apparatus for estimating a road surface state on the basis of a sound that is generated by a tire while a vehicle is running, road surface luminance information, and other information and a road surface friction state estimating apparatus, a road surface state physical quantity calculating apparatus, and a road surface state announcing apparatus that relate to the above road surface state estimating apparatus.
2. Description of the Related Art
Apparatus for estimating a road surface state using a sound that is generated by a tire were proposed (JP-A-6-138018 and JP-A-7-156782). These apparatus estimate a road surface state using a neural network by FFT-analyzing a sound that is generated by a tire and employing resulting frequency components of the tire-generated sound as inputs.
An apparatus was proposed in JP-A-8-327530 in which feature quantities representing road surface states such as power spectrum distributions of horizontal and vertical polarization images of images obtained by shooting road surfaces with a camera are detected and road surface friction coefficients, that is, coefficients of friction between a road surface and a tire, are stored in advance so as to be correlated with plural sets of feature quantities that represent different road surface states. A road surface friction coefficient is estimated on the basis of detected feature quantities representing a road surface state and the road surface friction coefficients that are stored so as to be correlated with the plural sets of feature quantities representing the different road surface states.
However, in the former apparatus, since a tire-generated sound is FFT-analyzed and resulting frequency components are used as inputs, the input frequency components cover a wide frequency range, as a result of which a long calculation time is needed and a considerable number of errors occur. Therefore, even if these apparatus are mounted on a vehicle actually, it is difficult for them to satisfy requirements.
In the apparatus disclosed in JP-A-8-327530, road surface friction coefficients are stored in advance so as to be correlated with plural sets of feature quantities representing different road surface states and a road surface friction coefficient is estimated on the basis of detected feature quantities representing a road surface state and the road surface friction coefficients that are stored so as to be correlated with the plural sets of feature quantities representing the different road surface states. As a result, a road surface friction coefficient can be estimated only within the confines of the stored road surface states and feature quantities. Therefore, a road surface friction coefficient cannot be estimated accurately if the stored road surface states and feature quantities are incorrect.